Fractures are one of the most common large-organ, traumatic injuries, and osteoporosis-related fractures are the fastest growing health care problem of aging. Fracture healing can be considered a complex trait that is defined by the regain in mechanical competence that allows resumption of weight bearing. As a complex trait, fracture healing is the result of the functional contributions of multiple cell types. Many individal phenotypic properties, such as the amount of mineralized tissue and structure of the callus, contribute to this complex trait, and each property is affected by interactions between multiple genetic and environmental factors. Our hypothesis is that a systems-network approach to the study of fracture healing under differing genetic and environmental conditions can be used to identify the central elements that contribute to this complex trait. Environmental variability of fracture healing will be modeled using parathyroid hormone (PTH) treatment, which enhances healing, and phosphate deficiency, which mimics rickets and inhibits healing. Genetic variability in fracture healing will be modeled using three inbred strains of mice with well characterized differences in bone quality. The first aim of the proposed work is to establish the functional relationships among specific structural features of the callus, cell and tissue types, and specific biological processes that contribute to the rate of regain of the mechanical properties of the fractured bone. This will be achieved by histological analysis, micro- computed tomography, and biomechanical testing to quantify the temporal changes in phenotypic properties of the fracture callus at the organ-, tissue-, and cellular levels. Multivariate regression analyses and path analyses will then be used to identify the functional dependencies among various phenotypic properties and to their relationship to regain in strength. The second aim is to identity the differentially expressed genes that contribute to fracture healing as a trait. Global transcriptionl profiling and multiple bioinformatics approaches will be used to define the primary transcription factors, biological and molecular process, and signal transduction pathways that are altered during fracture healing and in response to genetic variability and environmental perturbation. The causal relationships between the differentially expressed genes groups and the various phenotypic properties will be identified and will be used to define the molecular functions that control these phenotypic properties. In aggregate, these studies will identify both clinically useable correlates to assess healing and molecular targets to promote healing.